Abstract
Blasting performance is influenced by mechanical and structural properties of the rock, on one side, and blast design parameters on the other. This paper describes a new methodology to assess rock mass quality from drill-monitoring data to guide blasting in open pit operations. Principal component analysis has been used to combine measurement while drilling (MWD) information from two drill rigs; corrections of the MWD parameters to minimize external influences other than the rock mass have been applied. First, a Structural factor has been developed to classify the rock condition in three classes (massive, fractured and heavily fractured). From it, a structural block model has been developed to simplify the recognition of rock classes. Video recording of the inner wall of 256 blastholes has been used to calibrate the results obtained. Secondly, a combined strength-grade factor has been obtained based on the analysis of the rock type description and strength properties from geology reports, assaying of drilling chips (ore/waste identification) and 3D unmanned aerial vehicle reconstructions of the post-blast bench face. Data from 302 blastholes, comprised of 26 blasts, have been used for this analysis. From the results, four categories have been identified: soft-waste, hard-waste, transition zone and hard-ore. The model determines zones of soft and hard waste rock (schisted sandstone and limestone, respectively), and hard ore zones (siderite rock type). Finally, the structural block model has been combined with the strength-grade factor in an overall rock factor. This factor, exclusively obtained from drill monitoring data, can provide an automatic assessment of rock structure, strength, and waste/ore identification.
Highlights
Mining consists of several unit operations linked to each other, and the performance of the initial stages pre-conditions the downstream unit operations in the production cycle (Ghosh 2017)
About Measurement while drilling (MWD) interpretation on the structural rock condition, for rotary-percussive drilling, Schunnesson (1997) proposed a methodology to estimate the RQD index based on the penetration rate and torque pressure, and their variation, that shows a close correlation with the presence of discontinuities; Peng et al (2005) and Tang (2006) developed a method to measure void/fractures in tunnel roofs from bolt drilling; van Eldert et al (2020) correlated the MWD data to the RQD index and suggested an approach on the use of this technology for rock support design to improve cost efficiency in tunneling projects
This paper develops a new methodology for a sound rock characterization based on two new indexes from MWD records: the first one classifies the structural condition of the rock from the variability of the MWD parameters and a discontinuity factor by using principal components analysis (PCA); the second represents a combination of the strength properties and iron content of the rock, based on the combination of MWD parameters
Summary
Mining consists of several unit operations linked to each other, and the performance of the initial stages (drilling, charging and blasting) pre-conditions the downstream unit operations in the production cycle (Ghosh 2017). Few widely spaced holes are usually logged and the ground conditions between them are interpolated (Schunnesson 1997) This often leads to a largescale characterization of the rock mass, and to an inaccurate knowledge of the mechanical and structural rock mass properties at a small scale (e.g. a bench or a block to be blasted). About MWD interpretation on the structural rock condition, for rotary-percussive drilling, Schunnesson (1997) proposed a methodology to estimate the RQD index based on the penetration rate and torque pressure, and their variation, that shows a close correlation with the presence of discontinuities; Peng et al (2005) and Tang (2006) developed a method to measure void/fractures in tunnel roofs from bolt drilling; van Eldert et al (2020) correlated the MWD data to the RQD index and suggested an approach on the use of this technology for rock support design to improve cost efficiency in tunneling projects. The structural block model has been combined with the strength-grade Factor in an overall novel Rock Factor that, exclusively based on drill monitoring data, can provide a blast ability assessment based on the rock structure, strength and waste/ore identification
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
